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Séminaire Vision artificielle / Équipe Willow

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Three-Dimensional Computer Vision: Challenges and Opportunities
Jean Ponce (ENS)

12 octobre 2005

This talk addresses two of the main challenges of computer vision: automatically identifying three-dimensional (3D) objects in photographs despite arbitrary viewpoint variations, occlusion, and clutter; and recovering accurate models of 3D shapes observed in multiple images. I will first present a new approach to object recognition that combines local invariants with global geometric constraints to construct 3D object models from multiple images and/or stereo views and effectively identify them in heavily cluttered photographs taken from unknown viewpoints. I will then discuss a novel algorithm that uses the geometric and photometric constraints associated with multiple calibrated photographs to construct high-quality solid models of complex 3D shapes in the form of carved visual hulls. I will conclude with a brief discussion of exciting new application domains and wide open research issues.
Joint work with Yasutaka Furukawa, Akash Kushal, Svetlana Lazebnik, Fred Rothganger, and Cordelia Schmid.

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Jean Ponce Jean Ponce (ENS)